Classifying breast cancer cells by hypoxic and normoxic condition
A machine learning classifier that tells hypoxic from normoxic tumour cells using biological data.
A machine learning classifier that tells hypoxic from normoxic tumour cells using biological data.
Building a 20k-tweet and 500-article corpus to study how the public and the media frame artificial intelligence.
A simulation of the three-dimensional Ising model using both Simulated Annealing and the Wolff cluster algorithm.
Generating Most Excitatory Inputs for single neurons in mouse visual cortex with CNNs, benchmarked against Gabor filters.
Turning sign language videos into 3×3 frame grids so that a CNN can classify them as single images.
Predicting TP53 mutation status from CCLE transcriptomics with tree-based models, at ~81% F1-score.
Published in CIBB 2025 — 20th International Conference on Computational Intelligence Methods for Bioinformatics and Biostatistics, Politecnico di Milano, 2025
Extending the CellOracle framework with enrichment-based methods to make inferred gene regulatory networks more biologically interpretable.
Published in bioRxiv (under review), 2026
A Python framework for gene set scoring in bulk and single-cell RNA-seq, bringing together 18 scoring methods behind one interface, with built-in reliability analysis.
Published:
Presentation of my work on enrichment-based methods for Gene Regulatory Network reconstruction, extending the CellOracle framework with single-cell RNA-seq and ATAC-seq data to improve the biological interpretability of the inferred networks.